Green Finance, Climate Policy Uncertainty, and Ecological Carrying Capacity Dynamics in G20 Economies: Evidence from Load Capacity Factor Panel Analysis

Authors

  • Md Qamruzzaman

    School of Business and Economics, United International University, Dhaka 1212, Bangladesh

  • Syed Nazmus Sakib

    School of Engineering, Faculty of Science and Engineering, Macquarie University, Sydney 2109, Australia

  • Abdulateif A. Almulhim

    Finance Department, School of Business, King Faisal University, Hofuf 31982, Saudi Arabia

  • Abdullah A. Aljughaiman

    Finance Department, School of Business, King Faisal University, Hofuf 31982, Saudi Arabia

DOI:

https://doi.org/10.30564/re.v8i4.13687
Received: 24 June 2026 | Revised: 21 July 2026 | Accepted: 28 July 2026 | Published Online: 26 August 2026

Abstract

Carbon-based indicators do not show whether ecosystems can generate sufficient biocapacity to fulfil human needs, and the G20 economies account for a large portion of the global ecological burden. This study analyses the load capacity factor (LCF) of 19 G20 economies between 2000 and 2022, measured as biocapacity divided by the ecological footprint. It examines the long-run association between green bond issuance and ecological carrying capacity, as well as the moderating role of climate policy uncertainty (CPU) in this association. The analysis includes Pesaran cross-sectional dependence and slope heterogeneity tests, Cross-sectionally Augmented Im, Pesaran, and Shin (CIPS) and Cross-sectionally Augmented Dickey-Fuller (CADF) unit-root tests, Fourier-Shin cointegration, Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) estimation, Augmented Mean Group (AMG), Common Correlated Effects Mean Group (CCEMG) robustness checks, and Konya bootstrap Granger-causality tests, and conditional marginal-effect analysis for the GB_GDP × CPU interaction. The main CS-ARDL results show a positive long-run association for green bond issuance (β = 0.182, p < 0.01) and a negative association for the CPU (β = −0.011, p < 0.01). The interaction term is negative (β = −0.004, p < 0.05), indicating that the green bond-LCF association weakens as policy uncertainty increases. The conditional marginal effects become statistically indistinguishable from zero near the upper tail of the CPU distribution. The Konya results indicate heterogeneous country-level temporal patterns rather than uniform structural causality. Overall, green finance is associated with a stronger ecological carrying capacity when climate policy settings are stable and institutional conditions support long-term ecological investment.

Keywords:

Ecological Carrying Capacity; Load Capacity Factor; Biocapacity; Ecological Footprint; Green Bonds; Climate Policy Uncertainty; G20 Economies

References

[1] International Energy Agency, 2023. World Energy Outlook 2023. Available from: https://www.iea.org/reports/world-energy-outlook-2023 (cited 12 June 2026).

[2] Siche, R., Pereira, L., Agostinho, F., et al., 2010. Convergence of ecological footprint and emergy analysis as a sustainability indicator of countries: Peru as case study. Communications in Nonlinear Science and Numerical Simulation. 15(10), 3182–3192. DOI: https://doi.org/10.1016/j.cnsns.2009.10.027

[3] Climate Bonds Initiative, 2022. Sustainable Debt Tops $1 Trillion in Record Breaking 2021, with Green Growth at 75%: New Report. Available from: https://www.climatebonds.net/news-events/blog/sustainable-debt-tops-1-trillion-record-breaking-2021-green-growth-75-new-report (cited 12 June 2026).

[4] Dixit, A.K., Pindyck, R.S., 1994. Investment under Uncertainty. Princeton University Press: Princeton, NJ, USA.

[5] Rockström, J., Steffen, W., Noone, K., et al., 2009. A safe operating space for humanity. Nature. 461(7263), 472–475. DOI: https://doi.org/10.1038/461472a

[6] Annor, L.D.J., Robaina, M., Vieira, E., 2024. Climbing the green ladder in Sub-Saharan Africa: Dynamics of financial development, green energy, and load capacity factor. Environment Systems and Decisions. 44(3), 607–623. DOI: https://doi.org/10.1007/s10669-023-09959-2

[7] Javed, A., Usman, M., Rapposelli, A., 2025. Transition toward a sustainable future: Exploring the role of green investment, environmental policy, and financial development in the context of load capacity factor in G-7 countries. Sustainable Development. 33(2), 1589–1609. DOI: https://doi.org/10.1002/sd.3192

[8] Karlilar Pata, S., Pata, U.K., 2025. Comparative analysis of the impacts of solar, wind, biofuels and hydropower on load capacity factor and sustainable development index. Energy. 319, 134991. DOI: https://doi.org/10.1016/j.energy.2025.134991

[9] Uzar, U., Eyuboglu, K., 2025. Testing the load capacity curve for deforestation: A critical investigation using novel methods for the United States. Forest Policy and Economics. 178, 103579. DOI: https://doi.org/10.1016/j.forpol.2025.103579

[10] Senturk, N.K., Bayraktar, Y., Recepoglu, M., et al., 2025. The effects of sub-components of economic freedom on load capacity factor: Empirical analysis for MENA countries. Journal of Environmental Management. 380, 124956. DOI: https://doi.org/10.1016/j.jenvman.2025.124956

[11] Shah, S.S., Nakouwo, S.N., Sobirjonovna, G.M., et al., 2025. Exploring the sustainability impact of green bonds on ecological and resource capacities. Renewable Energy. 243, 122590. DOI: https://doi.org/10.1016/j.renene.2025.122590

[12] Tolliver, C., Keeley, A.R., Managi, S., 2020. Drivers of green bond market growth: The importance of nationally determined contributions to the Paris Agreement and implications for sustainability. Journal of Cleaner Production. 244, 118643. DOI: https://doi.org/10.1016/j.jclepro.2019.118643

[13] Flammer, C., 2021. Corporate green bonds. Journal of Financial Economics. 142(2), 499–516. DOI: https://doi.org/10.1016/j.jfineco.2021.01.010

[14] Svirydzenka, K., 2016. Introducing a New Broad-Based Index of Financial Development. International Monetary Fund: Washington, DC, USA. DOI: https://doi.org/10.5089/9781513583709.001

[15] Shah, S.S., Murodova, G., Khan, A., 2025. Contribution of green bonds and green growth in clean energy capacity under the moderating role of political stability. Renewable Energy. 246, 122888. DOI: https://doi.org/10.1016/j.renene.2025.122888

[16] Kartal, M.T., Pata, U.K., Alola, A.A., 2025. Impact of green bonds on CO2 emissions and disaggregated level renewable electricity in China and the United States of America. Humanities and Social Sciences Communications. 12, 350. DOI: https://doi.org/10.1057/s41599-025-04696-0

[17] Altaf, A., Anwar, M.A., Shahzad, U., et al., 2025. Exploring the nexus among green finance, renewable energy and environmental sustainability: Evidence from OECD economies. Renewable Energy. 244, 122589. DOI: https://doi.org/10.1016/j.renene.2025.122589

[18] Liu, X., Guo, W., 2025. Dynamic impact of green finance on renewable energy development: Based on scale, structure, and efficiency perspectives. Renewable Energy. 238, 121854. DOI: https://doi.org/10.1016/j.renene.2024.121854

[19] Omri, H., Jarraya, B., Kahia, M., 2025. Green finance for achieving environmental sustainability in G7 countries: Effects and transmission channels. Research in International Business and Finance. 74, 102691. DOI: https://doi.org/10.1016/j.ribaf.2024.102691

[20] Baker, S.R., Bloom, N., Davis, S.J., 2016. Measuring economic policy uncertainty. The Quarterly Journal of Economics. 131(4), 1593–1636. DOI: https://doi.org/10.1093/qje/qjw024

[21] Ahir, H., Bloom, N., Furceri, D., 2022. The World Uncertainty Index. NBER: Cambridge, MA, USA. DOI: https://doi.org/10.3386/w29763

[22] Ben-Salha, O., Ayad, H., 2025. Does climate policy uncertainty matter for sectoral environmental sustainability? Fresh evidence from the multiple threshold nonlinear ARDL model. Stochastic Environmental Research and Risk Assessment. 39(5), 1787–1804. DOI: https://doi.org/10.1007/s00477-025-02928-y

[23] Bildirici, M., Ersin, O.O., Olasehinde-Williams, G., 2025. Climate policy uncertainty, environmental regulatory arbitrage, and internal carbon leakage in the European Union: Fourier ARDL and causality analyses. Journal of the Knowledge Economy. 16, 13776–13810. DOI: https://doi.org/10.1007/s13132-025-02690-0

[24] Doganlar, M., Kizilkaya, O., Mike, F., et al., 2026. Does economic policy uncertainty matter for environmental degradation in emerging countries? Fresh evidence from Fourier bootstrap ARDL estimation. Journal of the Knowledge Economy. 17, 9244–9274. DOI: https://doi.org/10.1007/s13132-026-03163-8

[25] Bian, Z., Luo, M., 2025. Impact of climate policy uncertainty on enterprises' green technology innovation: Based on growth option theory. Sustainable Futures. 10, 101305. DOI: https://doi.org/10.1016/j.sftr.2025.101305

[26] Pata, U.K., 2025. Towards a sustainable future with renewable energy and load capacity factor: Institutions, technology, energy and climate policy uncertainties. Renewable Energy. 254, 123710. DOI: https://doi.org/10.1016/j.renene.2025.123710

[27] Pesaran, M.H., 2006. Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica. 74(4), 967–1012. DOI: https://doi.org/10.1111/j.1468-0262.2006.00692.x

[28] Eberhardt, M., Teal, F., 2010. Productivity Analysis in Global Manufacturing Production. University of Oxford: Oxford, UK. Available from: https://ora.ox.ac.uk/objects/uuid:f9d91b40-d8b7-402d-95eb-75a9cbdcd000 (cited 12 June 2026).

[29] Im, K.S., Pesaran, M.H., Shin, Y., 2003. Testing for unit roots in heterogeneous panels. Journal of Econometrics. 115(1), 53–74. DOI: https://doi.org/10.1016/S0304-4076(03)00092-7

[30] Pedroni, P., 2004. Panel cointegration: Asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory. 20(3), 597–625. DOI: https://doi.org/10.1017/S0266466604203073

[31] Kao, C., 1999. Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics. 90(1), 1–44. DOI: https://doi.org/10.1016/S0304-4076(98)00023-2

[32] Pesaran, M.H., 2004. General Diagnostic Tests for Cross Section Dependence in Panels. IZA Institute of Labor Economics: Bonn, Germany. Available from: https://www.iza.org/publications/dp/1240/general-diagnostic-tests-for-cross-section-dependence-in-panels (cited 12 June 2026).

[33] Pesaran, M.H., Yamagata, T., 2008. Testing slope homogeneity in large panels. Journal of Econometrics. 142(1), 50–93. DOI: https://doi.org/10.1016/j.jeconom.2007.05.010

[34] Pesaran, M.H., 2007. A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics. 22(2), 265–312. DOI: https://doi.org/10.1002/jae.951

[35] Chudik, A., Pesaran, M.H., 2015. Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors. Journal of Econometrics. 188(2), 393–420. DOI: https://doi.org/10.1016/j.jeconom.2015.03.007

[36] Tsong, C.C., Lee, C.F., Tsai, L.J., et al., 2016. The Fourier approximation and testing for the null of cointegration. Empirical Economics. 51(3), 1085–1113. DOI: https://doi.org/10.1007/s00181-015-1028-6

[37] Konya, L., 2006. Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling. 23(6), 978–992. DOI: https://doi.org/10.1016/j.econmod.2006.04.008

[38] Shi, S., Smith, L., 2025. Decoupling growth from degradation: A CS-ARDL and MMQR panel analysis of ecological footprints and sustainable economic growth. Frontiers in Environmental Science. 13. DOI: https://doi.org/10.3389/fenvs.2025.1604011

[39] Ersin, O.O., 2026. Decoupling of CO2 emissions from growth with energy transition and eco-innovations in OECD: Novel Fourier-CS-ARDL and Fourier-DH-causality analyses. Sustainability. 18(6), 2728. DOI: https://doi.org/10.3390/su18062728

[40] Grossman, G.M., Krueger, A.B., 1995. Economic growth and the environment. The Quarterly Journal of Economics. 110(2), 353–377. DOI: https://doi.org/10.2307/2118443

[41] Rogers, E.M., 2003. Diffusion of Innovations, 5th ed. Free Press: New York, NY, USA.

[42] Footprint Data Foundation, York University Ecological Footprint Initiative, and Global Footprint Network, 2023. Available from: https://data.footprintnetwork.org/ (cited 12 June 2026).

[43] World Bank, 2023. World Development Indicators. World Bank Group: Washington, DC, USA.

[44] Aiken, L.S., West, S.G., Reno, R.R., 1991. Multiple Regression: Testing and Interpreting Interactions. Sage: Thousand Oaks, CA, USA.

[45] Spiller, S.A., Fitzsimons, G.J., Lynch Jr., J.G., et al., 2013. Spotlights, floodlights, and the magic number zero: Simple effects tests in moderated regression. Journal of Marketing Research. 50(2), 277–288. DOI: https://doi.org/10.1509/jmr.12.0420

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How to Cite

Qamruzzaman, M., Sakib, S. N., Almulhim, A. A., & Aljughaiman, A. A. (2026). Green Finance, Climate Policy Uncertainty, and Ecological Carrying Capacity Dynamics in G20 Economies: Evidence from Load Capacity Factor Panel Analysis. Research in Ecology, 8(4), 339–358. https://doi.org/10.30564/re.v8i4.13687